High-resolution spatial and spatiotemporal modelling of air pollution using fixed site and mobile monitoring in a Canadian city.

Autor: Clark SN; Environmental and Social Epidemiology Section, Population Health Research Institute, St. George's, University of London, London, UK; Air Pollution Exposure Science Section, Water and Air Quality Bureau, Healthy Environments and Consumer Safety Branch, Health Canada, Government of Canada, Ottawa, Ontario, Canada., Kulka R; Air Pollution Exposure Science Section, Water and Air Quality Bureau, Healthy Environments and Consumer Safety Branch, Health Canada, Government of Canada, Ottawa, Ontario, Canada., Buteau S; Institut National de sante publique du Quebec (INSPQ), Quebec, Canada; École de santé publique, Département de santé environnementale et santé au travail, Université de Montréal, Québec, Canada; Centre of Public Health Research, University of Montreal and CIUSSS du Centre-Sud-de-l'Île-de-Montréal, Montreal, Canada., Lavigne E; Populations Studies Division, Environmental Health Science and Research Bureau, Health Canada, Ottawa, Canada., Zhang JJY; Air Pollution Exposure Science Section, Water and Air Quality Bureau, Healthy Environments and Consumer Safety Branch, Health Canada, Government of Canada, Ottawa, Ontario, Canada., Riel-Roberge C; Direction de santé publique, Centre intégré universitaire de santé et de services sociaux (CIUSSS) de la Capitale-Nationale, Quebec City, Quebec, Canada., Smargiassi A; Institut National de sante publique du Quebec (INSPQ), Quebec, Canada; École de santé publique, Département de santé environnementale et santé au travail, Université de Montréal, Québec, Canada; Centre of Public Health Research, University of Montreal and CIUSSS du Centre-Sud-de-l'Île-de-Montréal, Montreal, Canada., Weichenthal S; Air Pollution Exposure Science Section, Water and Air Quality Bureau, Healthy Environments and Consumer Safety Branch, Health Canada, Government of Canada, Ottawa, Ontario, Canada; Department of Epidemiology, Biostatistics, and Occupational Health, McGill University, Montreal, Quebec, Canada., Van Ryswyk K; Air Pollution Exposure Science Section, Water and Air Quality Bureau, Healthy Environments and Consumer Safety Branch, Health Canada, Government of Canada, Ottawa, Ontario, Canada. Electronic address: Keith.VanRyswyk@hc-sc.gc.ca.
Jazyk: angličtina
Zdroj: Environmental pollution (Barking, Essex : 1987) [Environ Pollut] 2024 Sep 01; Vol. 356, pp. 124353. Date of Electronic Publication: 2024 Jun 10.
DOI: 10.1016/j.envpol.2024.124353
Abstrakt: The development of high-resolution spatial and spatiotemporal models of air pollutants is essential for exposure science and epidemiological applications. While fixed-site sampling has conventionally provided input data for statistical predictive models, the evolving mobile monitoring method offers improved spatial resolution, ideal for measuring pollutants with high spatial variability such as ultrafine particles (UFP). The Quebec Air Pollution Exposure and Epidemiology (QAPEE) study measured and modelled the spatial and spatiotemporal distributions of understudied pollutants, such as UFPs, black carbon (BC), and brown carbon (BrC), along with fine particulate matter (PM 2.5 ), nitrogen dioxide (NO 2 ), and ozone (O 3 ) in Quebec City, Canada. We conducted a combined fixed-site (NO 2 and O 3 ) and mobile monitoring (PM 2.5 , BC, BrC, and UFPs) campaign over 10-months. Mobile monitoring routes were monitored on a weekly basis between 8am-10am and designed using location/allocation modelling. Seasonal fixed-site sampling campaigns captured continuous 24-h measurements over two-week periods. Generalized Additive Models (GAMs), which combined data on pollution concentrations with spatial, temporal, and spatiotemporal predictor variables were used to model and predict concentration surfaces. Annual models for PM 2.5 , NO 2 , O 3 as well as seven of the smallest size fractions in the UFP range, had high out of sample predictive accuracy (range r 2 : 0.54-0.86). Varying spatial patterns were observed across UFP size ranges measured as Particle Number Counts (PNC). The monthly spatiotemporal models for PM 2.5 (r 2  = 0.49), BC (r 2  = 0.27), BrC (r 2  = 0.29), and PNC (r 2  = 0.49) had moderate or moderate-low out of sample predictive accuracy. We conducted a sensitivity analysis and found that the minimum number of 'n visits' (mobile monitoring sessions) required to model annually representative air pollution concentrations was between 24 and 32 visits dependent on the pollutant. This study provides a single source of exposure models for a comprehensive set of air pollutants in Quebec City, Canada. These exposure models will feed into epidemiological research on the health impacts of ambient UFPs and other pollutants.
Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.
(Copyright © 2024 The Authors. Published by Elsevier Ltd.. All rights reserved.)
Databáze: MEDLINE
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